Ulteriori informazioni
Learn how to build your own computer vision (CV) applications quickly and easily with SimpleCV, an open source framework written in Python. Through examples of real-world applications, this hands-on guide introduces you to basic CV techniques for collecting, processing, and analyzing streaming digital images. You'll then learn how to apply these methods with SimpleCV, using sample Python code. All you need to get started is a Windows, Mac, or Linux system, and a willingness to put CV to work in a variety of ways. Programming experience is optional. Capture images from several sources, including webcams, smartphones, and Kinect Filter image input so your application processes only necessary information Manipulate images by performing basic arithmetic on pixel values Use feature detection techniques to focus on interesting parts of an image Work with several features in a single image, using the NumPy and SciPy Python libraries Learn about optical flow to identify objects that change between two image frames Use SimpleCV's command line and code editor to run examples and test techniques
Sommario
Preface
Chapter 1: Introduction
Chapter 2: Getting to Know the SimpleCV Framework
Chapter 3: Image Sources
Chapter 4: Pixels and Images
Chapter 5: The Impact of Light
Chapter 6: Image Arithmetic
Chapter 7: Drawing on Images
Chapter 8: Basic Feature Detection
Chapter 9: FeatureSet Manipulation
Chapter 10: Advanced Features
Advanced Shell Tips
Cameras and Lenses
Advanced Features
Info autore
Nathan Oostendorp has 15 of experience on running open source communities, being one of the founders of the website Slashdot , the site director for SourceForge and the creator of online communities PerlMonks and Everything2.
Riassunto
SimpleCV is a cross platform (Windows, Macintosh, Linux) framework in Python that makes writing computer vision applications quick and easy.
